diff --git a/src/toolbox_scs/detectors/hrixs.py b/src/toolbox_scs/detectors/hrixs.py
index 297cb900c9211c7e46f803c73bb05deeccf446c4..1523757297e58f981bcbc9f83f1049da27da4316 100644
--- a/src/toolbox_scs/detectors/hrixs.py
+++ b/src/toolbox_scs/detectors/hrixs.py
@@ -234,12 +234,16 @@ class hRIXS:
         self.Y_RANGE = np.s_[:]
 
         # centroid
+        self.C_METHOD='manual'
         self.THRESHOLD = None  # pixel counts above which a hit candidate is assumed
         self.STD_THRESHOLD = 3.5  # same as THRESHOLD, in standard deviations
-        self.DBL_THRESHOLD = 0.1  # factor used for double hits in centroid_one
+        self.DBL_THRESHOLD = 5  # factor used for double hits in centroid_one
+
+
         self.CURVE_A = 0  # curvature parameters as determined elsewhere
         self.CURVE_B = 0
 
+
         # integral
         self.BINS = 100
 
@@ -442,7 +446,7 @@ class hRIXS:
                     dres.append((mx, my))
         return res, dres
 
-    def centroid(self, data, bins=None, method='auto'):
+    def centroid(self, data, bins=None, method=None):
         """calculate a spectrum by finding the centroid of individual photons
 
         This takes the `xarray.Dataset` `data` and returns a copy of it, with
@@ -462,6 +466,8 @@ class hRIXS:
         """
         if bins is None:
             bins = self.BINS
+        if method is None:
+            method = self.C_METHOD
         ret = np.zeros((len(data["hRIXS_det"]), bins))
         retd = np.zeros((len(data["hRIXS_det"]), bins))
         total_hits = np.zeros((len(data["hRIXS_det"])))